TY - JOUR
T1 - A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy
AU - Hardcastle, Nicholas
AU - Tomé, Wolfgang A.
AU - Cannon, Donald M.
AU - Brouwer, Charlotte L.
AU - Wittendorp, Paul W.H.
AU - Dogan, Nesrin
AU - Guckenberger, Matthias
AU - Allaire, Stéphane
AU - Mallya, Yogish
AU - Kumar, Prashant
AU - Oechsner, Markus
AU - Richter, Anne
AU - Song, Shiyu
AU - Myers, Michael
AU - Polat, Bülent
AU - Bzdusek, Karl
N1 - Funding Information:
Nicholas Hardcastle was funded in part by a grant from Philips Radiation Oncology Systems awarded to Prof. Wolfgang Tomé. Karl Bzdusek and Stéphane Allaire are current employees of Philips Radiation Oncology Systems and Philips Research Medisys, respectively. SA however performed the work for this manuscript whilst employed at Princess Margaret Hospital, ON, Canada.
PY - 2012/6/15
Y1 - 2012/6/15
N2 - Background: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs.Methods: Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility.Results: Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27% (12/44) of the GTVs required major edits.Conclusion: DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician.
AB - Background: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs.Methods: Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility.Results: Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27% (12/44) of the GTVs required major edits.Conclusion: DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician.
KW - Adaptive radiotherapy
KW - Deformable image registration
KW - Head and neck cancer
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U2 - 10.1186/1748-717X-7-90
DO - 10.1186/1748-717X-7-90
M3 - Article
C2 - 22704464
AN - SCOPUS:84862207727
SN - 1748-717X
VL - 7
JO - Radiation Oncology
JF - Radiation Oncology
IS - 1
M1 - 90
ER -